In my exploratory data analysis of the river Rhine, I produced tables and graphs on various data sets of discharge at different stations along the course of the river Rhine. The anaysis hypothesis, suggests falling summer discharge and increasesing winter dischagre, due to climate change and it knock on effects on snow depths in mountains regions and incresed evapotranspiration during summer months.
brocken down by various months and various stations along the river, it is clear were data is missing due to -999 value
| sname | variable | value |
|---|---|---|
| REES | mean_day | 2029 |
| DUES | mean_day | 2126 |
| KOEL | mean_day | 2086 |
| ANDE | mean_day | 2039 |
| KAUB | mean_day | 1654 |
| MAIN | mean_day | 1612 |
| SPEY | mean_day | 1276 |
| WORM | mean_day | 1415 |
| MAXA | mean_day | 1245 |
| RHEI | mean_day | 1031 |
| LOBI | mean_day | 2214 |
| BASE | mean_day | 1047 |
| BASR | mean_day | 1044 |
| BASS | mean_day | 1042 |
| RHEM | mean_day | 1031 |
| REKI | mean_day | 441 |
| NEUF | mean_day | 369 |
| DOMA | mean_day | 89 |
| FELS | mean_day | 82 |
| DIER | mean_day | 230 |
| REES | sd_day | 1351 |
| DUES | sd_day | 1078 |
| KOEL | sd_day | 1039 |
| ANDE | sd_day | 1057 |
| KAUB | sd_day | 745 |
| MAIN | sd_day | 707 |
| SPEY | sd_day | 518 |
| WORM | sd_day | 599 |
| MAXA | sd_day | 544 |
| RHEI | sd_day | 436 |
| LOBI | sd_day | 1132 |
| BASE | sd_day | 444 |
| BASR | sd_day | 457 |
| BASS | sd_day | 459 |
| RHEM | sd_day | 435 |
| REKI | sd_day | 193 |
| NEUF | sd_day | 168 |
| DOMA | sd_day | 200 |
| FELS | sd_day | 225 |
| DIER | sd_day | 167 |
| REES | min_day | -999 |
| DUES | min_day | 464 |
| KOEL | min_day | 401 |
| ANDE | min_day | 560 |
| KAUB | min_day | 482 |
| MAIN | min_day | 460 |
| SPEY | min_day | 364 |
| WORM | min_day | 415 |
| MAXA | min_day | -999 |
| RHEI | min_day | 259 |
| LOBI | min_day | 575 |
| BASE | min_day | 319 |
| BASR | min_day | 272 |
| BASS | min_day | 272 |
| RHEM | min_day | 315 |
| REKI | min_day | 120 |
| NEUF | min_day | 104 |
| DOMA | min_day | -999 |
| FELS | min_day | -999 |
| DIER | min_day | 40 |
| REES | max_day | 11700 |
| DUES | max_day | 11000 |
| KOEL | max_day | 10900 |
| ANDE | max_day | 10400 |
| KAUB | max_day | 7160 |
| MAIN | max_day | 6920 |
| SPEY | max_day | 4410 |
| WORM | max_day | 5400 |
| MAXA | max_day | 4340 |
| RHEI | max_day | 4219 |
| LOBI | max_day | 13000 |
| BASE | max_day | 3661 |
| BASR | max_day | 5530 |
| BASS | max_day | 5530 |
| RHEM | max_day | 4220 |
| REKI | max_day | 1872 |
| NEUF | max_day | 1167 |
| DOMA | max_day | 1563 |
| FELS | max_day | 1563 |
| DIER | max_day | 2028 |
| REES | median | 1920 |
| DUES | median | 1889 |
| KOEL | median | 1850 |
| ANDE | median | 1790 |
| KAUB | median | 1500 |
| MAIN | median | 1472 |
| SPEY | median | 1180 |
| WORM | median | 1300 |
| MAXA | median | 1145 |
| RHEI | median | 954 |
| LOBI | median | 1950 |
| BASE | median | 979 |
| BASR | median | 968 |
| BASS | median | 969 |
| RHEM | median | 955 |
| REKI | median | 402 |
| NEUF | median | 330 |
| DOMA | median | 83 |
| FELS | median | 79 |
| DIER | median | 172 |
This table shows a plots of summary statitics of all stations over the period of all data collected, it shows the spread of the data. This could be important in being able to catagorise stations into specific subsets, such as differences in mean values, or the differences in the range, hence patterens could be deduced. Data with incorrect values from previous table has been removed.
To show and identify points in time when maximum points and minimum points were reached in the stations run off data, I created interactive plots of each station, it is also easty to see if there is correlation between station or not
This graph shows changes in total monthly runoff at three selected measurement stations, at different points of altitude along the river, DOMA and BASR are at higher altitudes, while KOEL is at a lower altitude, in the results it is easy to show the greater divergence of the mean at stations with higher altitude,(smaller in summer, greater in winter), this holds true for all stations. In selected different points on the river rhine, it would be important to ask such questions as, do other tributaries change overall results? And has there been any human activity near a station which would have an impact on the results ?
This graph shows that post 2000, the range of values of runoff are getting smaller at the sample stations ,moreover fewer outliers occur, whilst there is little significant change in the mean, this suggest the analysis hypothesis is correct, which predicted higher winter and lower summer runoff over the past 20 years relative to the whole time period of the data set
human inpacts on the river rhine have been extensive, from building of dams to use of water in waste treatment and agriculture, these influnces will ahve impacts on river runoff at different locations, hence identifing were and when dams and agriculutral impacts will be important indetermining the runn off as a function of time and displacement. Other major rivers in europe such as elbe could also be analysed to see if it follows similar patterns as the rhine.